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Quadrotor motion planning in complex environments leverage the concept ofsafe flight corridor (SFC) to facilitate static obstacle avoidance. Typically,SFCs are constructed through convex decomposition of the environment's freespace into cuboids, convex polyhedra, or spheres. However, when dealing with aquadrotor swarm, such SFCs can be overly conservative, substantially limitingthe available free space for quadrotors to coordinate. This paper presents anAlternating Minimization-based approach that does not require building aconservative free-space approximation. Instead, both static and dynamiccollision constraints are treated in a unified manner. Dynamic collisions arehandled based on shared position trajectories of the quadrotors. Staticobstacle avoidance is coupled with distance queries from the Octomap, providingan implicit non-convex decomposition of free space. As a result, our approachis scalable to arbitrary complex environments. Through extensive comparisons insimulation, we demonstrate a $60\%$ improvement in success rate, an average$1.8\times$ reduction in mission completion time, and an average $23\times$reduction in per-agent computation time compared to SFC-based approaches. Wealso experimentally validated our approach using a Crazyflie quadrotor swarm ofup to 12 quadrotors in obstacle-rich environments. The code, supplementarymaterials, and videos are released for reference.

AMSwarmX: Safe Swarm Coordination in CompleX Environments via Implicit Non-Convex Decomposition of the Obstacle-Free Space